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All Lessons
Free Lessons (3)
Introduction
Before We Start
Data Structures
Series Introduction
NaN Values in Series
Similarities in pandas and NumPy
Categorical Data in pandas
Exercise: Series in pandas
Solution: Series in pandas
Summary
Quiz: pandas Series
Series Deep Dive
Data Loading and Series Attributes
Operators and Dunder Methods
Aggregate Methods
Exercise: Aggregate Methods
Solution: Aggregate Methods
Conversion Methods
Manipulation Methods
Quiz: Methods in Series
Conditional Methods
Handling Missing Data
Other Manipulation Methods
Data Cleaning
Quiz: Duplicate values and NaN
Indexing Operations
Indexing Operations (.iloc)
Exercise: Data Manipulation and Indexing
Solution: Data Manipulation and Indexing
Quiz: Indexing, Manipulation Methods, and Data Cleaning
String Manipulation
Optimizing Manipulations Using Cython
Date and Time Manipulation
Dates in the Index
Quiz: String Manipulation, Date-Time Manipulation, and DT Indexing
Plotting with a Series: Histogram, Box Plot, and Kernel Density
Plotting with a Series: Line, Bar, and Pie Plots
Categorical Manipulation
Quiz: Plotting and Categorical Data
DataFrames
Introduction to DataFrames
Similarities between Series and DataFrame
Math Methods on DataFrames
Quiz: DataFrames and Math Methods on DataFrames
Exercise: DataFrames in pandas
Solution: DataFrames in pandas
Looping and Aggregation
The apply() Method
Exercise: Looping, Aggregation and apply() Method
Solution: Looping, Aggregation, and apply() Method
Columns Types, .assign, and Memory Usage
Creating and Updating Columns
Dealing with Missing and Duplicated Data
Quiz: Missing and Duplicated Data
Sorting Columns and Indexes
Filtering and Indexing Operations
Indexing by Position
Indexing by Name
Filtering with Function and .loc
Line and Bar Plots
Scatter, Area, and Stacked Bar Plots
Exercise: Sorting, Columns, Filtering, and Indexing Operations.
Solution: Sorting, Columns, Filtering, and Indexing Operations
Exercise: Plotting
Solution: Plotting
Quiz: Sorting Columns, Filtering, and Indexing Operations.
Reshaping DataFrames with Dummies
Reshaping by Pivoting and Grouping
Aggregations
Manipulating Data
Grouping
More Aggregations
Cross-tabulation Deep Dive
Exercise: Reshaping/Aggregations
Solution: Reshaping/Aggregations
Quiz: Reshaping, Pivot Tables, Aggregations
Melting and Transposing Data
Stacking and Flattening Data
Quiz: Melting, Transposing, Stacking, and Unstacking Data
Working with Time Series
Adding Rows and Columns in a DataFrame
Joins in DataFrames
Joining Real-World Datasets
Quiz: Joining in pandas
Exporting Data to CSV and Excel
Exporting Data to Feather, SQL, and JSON
Styling DataFrames
Checking if DataFrames are Equal
Debugging Chains
Debugging apply (and friends)
Debugging Memory Usage and Timing Information
Wrapping Up
Conclusion
Appendix
Installation
Effective Data Manipulation with pandas
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Summary
Summary
See the advantages of Series and the pandas library.
We'll cover the following...
The Series object is
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